As part of that effort, Splunk also unfurled Splunk Cloud, an instance of its software that is deployed by Splunk on top of the Amazon Web Services cloud, which can also be tightly integrated with on-premise instances of Splunk. In addition, the company has expanded the storage capacity of Splunk Storm, a free cloud service for developers that provides up to 20GB per month.

That ability leverages a new analytics store, pivot functions, and support for data models that have all been added to this release of Splunk Enterprise.

Without having to master any particular programming language, Splunk Enterprise 6.0 allows users to define relationships between data sets that can be more easily visualized and manipulated. And because Splunk relies on a late-binding data model, Mehta says users can iteratively launch queries in real time based on the previous answer to a question against Splunk data, while sharing the data model they created with other end users.

Mehta says it’s one thing to be able to gather data to create a Big Data repository; actually turning all that information into actionable intelligence requires tools that everyone from data scientists to the average business user can easily comprehend and invoke is a different task altogether. After doing so, says Mehta, the average organization can derive the real business value from its investment in Big Data.